Prakash Panangaden
Prakash Panangaden is a computer scientist whose mathematics of probabilistic systems reaches into machine learning. Trained in physics, he earned a PhD at the University of Wisconsin–Milwaukee in 1980 and an MS in computer science at the University of Utah in 1985. After joining Cornell as an assistant professor in 1985, he moved to McGill University in 1990, coauthored work on bisimulation for labelled Markov processes in 1997 and 2002, and retired in 2024. A core member of Mila from 2018 to 2024, he coauthored the MICo state-similarity distance for deep reinforcement learning agents in 2021. The Royal Society elected him a Fellow in 2025 and the EATCS did in 2026, and he is an Honorary Professor in the School of Informatics at the University of Edinburgh.
- Now at
- McGill University and University of Edinburgh
- Born
- 1954
- Badges
Years link to their sources.
Timeline
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1980–1985
From physics to computer science
After physics degrees at IIT Kanpur and the University of Chicago, he earns a PhD in physics at the University of Wisconsin–Milwaukee in 1980, working on quantum field theory in curved spacetime. He then turns to computer science and earns an MS at the University of Utah in 1985.
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1985–2024
Faculty at Cornell and McGill
He joins the Department of Computer Science at Cornell University as an assistant professor in 1985, works on the semantics of concurrent programming languages, and coauthors Implementing Mathematics with the Nuprl Proof Development System in 1986. He moves to McGill University's School of Computer Science in 1990 and retires in 2024 after 34 years.
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1997–2009
Bisimulation for Markov processes
In 1997, he coauthors Bisimulation for Labelled Markov Processes with Richard Blute, Josée Desharnais and Abbas Edalat. In 2002, he coauthors A metric analogue of weak bisimulation with Desharnais, Vineet Gupta and Radha Jagadeesan. In 2009, he publishes the book Labelled Markov Processes.
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2013–2020
RSC and ACM fellowships
In 2013, he is elected a Fellow of the Royal Society of Canada, and in 2020 he is appointed a Fellow of the Association for Computing Machinery.
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2018–2024
Mila and the MICo distance
From 2018 to 2024, he is a core member of Mila, the Montreal Institute for Learning Algorithms, where he works on using metrics to enhance representation learning. In 2021, he coauthors MICo with Pablo Samuel Castro, Tyler Kastner and Mark Rowland, a behavioural distance over Markov decision process states for shaping the representations of deep reinforcement learning agents, published at NeurIPS.
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2025
Fellow of the Royal Society
In 2025, he is elected a Fellow of the Royal Society, the U.K.'s national academy of sciences. His methods for modelling and approximating systems with continuous state spaces have led to applications in probabilistic systems and machine learning.
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2026
Named an EATCS Fellow
In 2026, the European Association for Theoretical Computer Science names him a Fellow for contributions to the semantics and logic of probabilistic computation, with applications in systems modelling, verification and machine learning.
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As of October 2026
Honorary Professor at Edinburgh
Retired from McGill, he moves to Edinburgh, where he is an Honorary Professor in the School of Informatics. The Royal Society lists him as Professor Emeritus at McGill, and he is still active in research.
Career
- Since 1990McGill UniversityProfessor Emeritus
- NowUniversity of EdinburghHonorary Professor
- 2018–2024MilaCore Member
- 1985–1990Cornell UniversityAssistant Professor
Education
- 1985University of UtahMS
- 1980University of Wisconsin–MilwaukeePhD
- Indian Institute of Technology KanpurPhysics degree
- University of ChicagoPhysics degree
Sources and credits
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- Prof Prakash Panangaden | IIT Kanpur
- Prakash Panangaden | Mila
- Prakash Panangaden - Wikipedia
- Professor Emeritus Prakash Panangaden elected as Fellow of the Royal Society - McGill Reporter
- Prakash Panangaden FRS FRSC
- Professor Prakash Panangaden FRS | Royal Society Fellow
- MICo: Improved representations via sampling-based state similarity for Markov decision processes
- EATCS Fellows class of 2026 named


